Evaluation of clinical colon carcinoma using activity-based proteomic profiling

The evaluation of clinical tumor tissues is a valuable approach to discovering novel drug targets because of the direct relevance of human samples. We used activity-based proteomic profiling (ABPP) to study the differences in serine hydrolase activities from 12 matched pairs of clinical normal and tumor colon tissues. Unlike traditional proteomics or measures of mRNA abundance, ABPP actually quantifies enzymatic activities, a characteristic crucial for drug targeting. Several serine hydrolases were differentially active in tumor vs normal tissues, despite a lack of obvious corresponding alterations in protein expression. We identified one tumor-specific activity by mass spectrometry to be fibroblast activation protein (FAP), an integral membrane serine protease that has been reported to be present only in tumor stroma or during wound healing and absent in normal tissues. FAP activity was further found to be approximately twofold higher in stage III relative to stage II colon cancer, suggestive of a role in tumor progression. We were also able to identify other proteins, some of which had not been previously linked to cancer, which had higher activity in tumors. Our results demonstrate the applicability of ABPP for the efficient identification of multiple clinical disease targets.     

Immunofluorometric activity-based probe analysis of active KLK6 in biological fluids

Immunoassay measurements of human kallikrein-related peptidases (KLKs) such as prostate-specific antigen (KLK3) are of great value as diagnostic indices of cancer. Despite extensive knowledge of the abundance of immunoreactive KLKs in normal and cancer-related settings, there is little information available about the proportion of immunoreactive KLK that represents active enzyme in such samples. Using KLK6 as a prototype enzyme, we have developed an assay using a serine proteinase-targeted activity-based probe coupled to antibody capture. By employing activity-based labeling, we were able to quantify the proportion of enzymatically active relative to total immunoreactive KLK6 in crude cerebrospinal fluid from routine analyses and ascites fluid from ovarian cancer patients, as well as in supernatants from cancer cell lines. Our approach allowed monitoring of pro-KLK6 conversion to its active enzyme species and demonstrated that up to 5% of immunoreactive KLK6 detected in clinical samples represents active enzyme. We suggest that this new activity-based probe assay will prove of value as a complement to routine KLK immunoassay measurements for validating KLKs as cancer biomarkers.     

Fluorescent multiplexing of 3D spheroids: Analysis of biomarkers using automated immunohistochemistry staining platform and multispectral imaging

In preclinical cancer studies, three-dimensional (3D) cell spheroids and aggregates are preferred over monolayer cell cultures due to their architectural and functional similarity to solid tumors. We performed a proof-of-concept study to generate physiologically relevant and predictive preclinical models using non–small cell lung adenocarcinoma, and colon and colorectal adenocarcinoma cell line-derived 3D spheroids and aggregates. Distinct panels were designed to determine the expression profiles of frequently studied biomarkers of the two cancer subtypes. The lung adenocarcinoma panel included ALK, EGFR, TTF-1, and CK7 biomarkers, and the colon and colorectal adenocarcinoma panel included BRAF V600E, MSH2, MSH6, and CK20. Recent advances in immunofluorescence (IF) multiplexing and imaging technology enable simultaneous detection and quantification of multiple biomarkers on a single slide. In this study, we performed IF staining of multiple biomarkers per section on formalin-fixed paraffin-embedded 3D spheroids and aggregates. We optimized protocol parameters for automated IF and demonstrated staining concordance with automated chromogenic immunohistochemistry performed with validated protocols. Next, post-acquisition spectral unmixing of the captured fluorescent signals were utilized to delineate four differently stained biomarkers within a single multiplex IF image, followed by automated quantification of the expressed markers. This workflow has the potential to be adapted to preclinical high-throughput screening and drug efficacy studies utilizing 3D spheroids from cancer cell lines and patient-derived organoids. The process allows for cost, time, and resource savings through concurrent staining of several biomarkers on a single slide, the ability to study the interactions of multiple expressed proteins within a single region of interest, and enable quantitative assessment of biomarkers in cancer cells.     

Identification of putative serum glycoprotein biomarkers for human lung adenocarcinoma by multilectin affinity chromatography and LC-MS/MS

Glycoproteins in human serum play fundamental roles in many biological processes, and also have clinical value as biomarkers for disease progression and treatment. In this study, we isolated glycoproteins from the sera of three healthy individuals and three lung adenocarcinoma patients using multilectin affinity chromatography. The recovered glycoproteins were subjected to treatment with peptide-N-glycosidase F (PNGase F) and in-gel digestion by trypsin. Tryptic peptides were analyzed by nano-LC coupled to ESI-MS/MS and the MS/MS spectra were processed by Bioworks 3.2 and an in-house bioinformatics tool, ProtAn. Approximately 90% of the proteins identified contained more than one potential glycosylation site. Comparison of the serum glycoproteome of healthy and adenocarcinoma individuals revealed 38 cancer-selective proteins. Among them, 60% have previously been reported as low abundance proteins in human sera. We identified several cancer-selective proteins that have been previously characterized as potential indicators of lung cancer in serum or plasma, including haptoglobin (HP), inter-alpha-trypsin inhibitor heavy chain 4 (ITI-H4), complement C3 precursor, and leucine-rich alpha-2-glycoprotein. In addition, plasma kallikrein (KLKB1) and inter-alpha-trypsin inhibitor heavy chain 3 (ITI-H3) were identified as being potentially elevated in the lung cancer group, and were validated by Western blot analysis. Furthermore, approximately 18 kDa plasma kallirein protein fragment was detected at high levels in 25 out of 28 adenocarcinoma patients, while one of the eight normal individuals showed moderate positive. The results suggest that KLKB1 represents a potential candidate serum biomarker of lung cancer.     

Validation of a blood protein signature for non-small cell lung cancer

Background

CT screening for lung cancer is effective in reducing mortality, but there are areas of concern, including a positive predictive value of 4% and development of interval cancers. A blood test that could manage these limitations would be useful, but development of such tests has been impaired by variations in blood collection that may lead to poor reproducibility across populations.

Results

Blood-based proteomic profiles were generated with SOMAscan technology, which measured 1033 proteins. First, preanalytic variability was evaluated with Sample Mapping Vectors (SMV), which are panels of proteins that detect confounders in protein levels related to sample collection. A subset of well collected serum samples not influenced by preanalytic variability was selected for discovery of lung cancer biomarkers. The impact of sample collection variation on these candidate markers was tested in the subset of samples with higher SMV scores so that the most robust markers could be used to create disease classifiers. The discovery sample set (n = 363) was from a multi-center study of 94 non-small cell lung cancer (NSCLC) cases and 269 long-term smokers and benign pulmonary nodule controls. The analysis resulted in a 7-marker panel with an AUC of 0.85 for all cases (68% adenocarcinoma, 32% squamous) and an AUC of 0.93 for squamous cell carcinoma in particular. This panel was validated by making blinded predictions in two independent cohorts (n = 138 in the first validation and n = 135 in the second). The model was recalibrated for a panel format prior to unblinding the second cohort. The AUCs overall were 0.81 and 0.77, and for squamous cell tumors alone were 0.89 and 0.87. The estimated negative predictive value for a 15% disease prevalence was 93% overall and 99% for squamous lung tumors. The proteins in the classifier function in destruction of the extracellular matrix, metabolic homeostasis and inflammation.

Conclusions

Selecting biomarkers resistant to sample processing variation led to robust lung cancer biomarkers that performed consistently in independent validations. They form a sensitive signature for detection of lung cancer, especially squamous cell histology. This non-invasive test could be used to improve the positive predictive value of CT screening, with the potential to avoid invasive evaluation of nonmalignant pulmonary nodules.     

Identification of the Major Prostaglandin Glycerol Ester Hydrolase in Human Cancer Cells

Prostaglandin glycerol esters (PG-Gs) are produced as a result of the oxygenation of the endocannabinoid, 2-arachidonoylglycerol, by cyclooxygenase 2. Understanding the role that PG-Gs play in a biological setting has been difficult because of their sensitivity to enzymatic hydrolysis. By comparing PG-G hydrolysis across human cancer cell lines to serine hydrolase activities determined by activity-based protein profiling, we identified lysophospholipase A2 (LYPLA2) as a major enzyme responsible for PG-G hydrolysis. The principal role played by LYPLA2 in PGE₂-G hydrolysis was confirmed by siRNA knockdown. Purified recombinant LYPLA2 hydrolyzed PG-Gs in the following order of activity: PGE₂-G > PGF_2α-G > PGD₂-G; LYPLA2 hydrolyzed 1- but not 2-arachidonoylglycerol or arachidonoylethanolamide. Chemical inhibition of LYPLA2 in the mouse macrophage-like cell line, RAW264.7, elicited an increase in PG-G production. Our data indicate that LYPLA2 serves as a major PG-G hydrolase in human cells. Perturbation of this enzyme should enable selective modulation of PG-Gs without alterations in endocannabinoids, thereby providing a means to decipher the unique functions of PG-Gs in biology and disease.     

Circulating microRNAs as potential biomarkers for smoking-related interstitial fibrosis

Numerous efforts have been made to indentify reliable and predictive biomarkers to detect the early signs of smoking-induced lung disease. Using 6-month cigarette smoking in mice, we have established smoking-related interstitial fibrosis (SRIF). Microarray analyses and cytokine/chemokine biomarker measurements were made to select circulating microRNAs (miRNAs) biomarkers. We have demonstrated that specific miRNAs species (miR-125b-5p, miR-128, miR-30e, and miR-20b) were significantly changed, both in the lung tissue and in plasma, and exhibited mainstream (MS) exposure duration-dependent pathological changes in the lung. These findings suggested a potential use of specific circulating miRNAs as sensitive and informative biomarkers for smoking-induced lung disease.     

Circulating microRNAs as potential biomarkers for smoking-related interstitial fibrosis

Numerous efforts have been made to indentify reliable and predictive biomarkers to detect the early signs of smoking-induced lung disease. Using 6-month cigarette smoking in mice, we have established smoking-related interstitial fibrosis (SRIF). Microarray analyses and cytokine/chemokine biomarker measurements were made to select circulating microRNAs (miRNAs) biomarkers. We have demonstrated that specific miRNAs species (miR-125b-5p, miR-128, miR-30e, and miR-20b) were significantly changed, both in the lung tissue and in plasma, and exhibited mainstream (MS) exposure duration-dependent pathological changes in the lung. These findings suggested a potential use of specific circulating miRNAs as sensitive and informative biomarkers for smoking-induced lung disease.     

Proteomics analysis of human serum of patients with non-small-cell lung cancer reveals proteins as diagnostic biomarker candidates

Non-small-cell lung carcinomas (NSCLC) is the most common type of lung cancer and it has a poor prognosis, because overall survival after 5 years is 20–25% for all stages. Thus, it is extremely important to increase the survival rate in the early stages NSCLC by focusing on novel screening tests of cancer identifying specific biomarkers expression associated with a more accurate tumor staging and patient prognosis. In this study, we focused our attention on quantitative proteomics of three heavily glycosylated serum proteins: AMBP, α2 macroglobulin, and SERPINA1. In particular, we analyzed serum samples from 20 NSCLC lung adenocarcinoma cancer patients in early and advanced stages, and 10 healthy donors to obtain a relative quantification through the MRM analysis of these proteins that have shown to be markers of cancer development and progression. AMBP, α2 macroglobulin, and SERPINA1 were chosen because all of them possess endopeptidase inhibitor activity and play key roles in cancer. We observe a variation in the expression of these proteins linked to the stage of the disease. Therefore, we believe that proteins like α2 macroglobulin, αmicroglobulin/bikunin, and SERPINA1 could be useful biomarkers for early detection of lung cancer and in monitoring its evolution.     

Oxime esters as selective,covalent inhibitors of the serine hydrolase retinoblastoma-binding protein 9 (RBBP9)

We recently described a fluorescence polarization platform for competitive activity-based protein profiling (fluopol-ABPP) that enables high-throughput inhibitor screening for enzymes with poorly characterized biochemical activity. Here, we report the discovery of a class of oxime ester inhibitors for the unannotated serine hydrolase RBBP9 from a full-deck (200,000+ compound) fluopol-ABPP screen conducted in collaboration with the Molecular Libraries Screening Center Network (MLSCN). We show that these compounds covalently inhibit RBBP9 by modifying enzyme’s active site serine nucleophile and, based on competitive ABPP in cell and tissue proteomes, are selective for RBBP9 relative to other mammalian serine hydrolases.     

Profiling serine hydrolase activities in complex proteomes

Serine hydrolases represent one of the largest and most diverse families of enzymes in higher eukaryotes, comprising numerous proteases, lipases, esterases, and amidases. The activities of many serine hydrolases are tightly regulated by posttranslational mechanisms, limiting the suitability of standard genomics and proteomics methods for the functional characterization of these enzymes. To facilitate the global analysis of serine hydrolase activities in complex proteomes, a biotinylated fluorophosphonate (FP-biotin) was recently synthesized and shown to serve as an activity-based probe for several members of this enzyme family. However, the extent to which FP-biotin reacts with the complete repertoire of active serine hydrolases present in a given proteome remains largely unexplored. Herein, we describe the synthesis and utility of a variant of FP-biotin in which the agent's hydrophobic alkyl chain linker was replaced by a more hydrophilic poly(ethylene glycol) moiety (FP-peg-biotin). When incubated with both soluble and membrane proteomes for extended reaction times, FP-biotin and FP-peg-biotin generated similar "maximal coverage" serine hydrolase activity profiles. However, kinetic analyses revealed that several serine hydrolases reacted at different rates with each FP agent. These rate differences were exploited in studies that used the biotinylated FPs to examine the target selectivity of reversible serine hydrolase inhibitors directly in complex proteomes. Finally, a general method for the avidin-based affinity isolation of FP-biotinylated proteins was developed, permitting the rapid and simultaneous identification of multiple serine peptidases, lipases, and esterases. Collectively, these studies demonstrate that chemical probes such as the biotinylated FPs can greatly accelerate both the functional characterization and molecular identification of active enzymes in complex proteomes.     

不同病理分期肺腺癌患者血清代谢组学研究

肺癌是当今世界最常见的恶性肿瘤之一,其新发率和死亡率多年来都居于各类癌症之首,其中85%的肺癌都是非小细胞癌,而腺癌又是最常见的非小细胞癌。肺癌的高隐匿性是造成其高死亡率的最主要原因,因此为肺癌的早期诊断和病理分期寻求高效可靠的方法是十分必要的。代谢组学揭示了小分子代谢物的一系列变化,反映了生命活动的最终状态,因此也能直接反映疾病不同发展阶段的病理生理变化。本研究利用核磁共振氢谱(1H-NMR),对在我院就诊的27例不同病理分期的肺腺癌患者和13例健康志愿者进行了血清代谢物分析,运用正交偏最小二乘判别分析(OPLS-DA)对1H-NMR数据进行建模,单变量统计分析对模型进行评价。结果表明肺腺癌患者组的血清中有14种代谢物出现明显差异,其中丙酮酸、丙氨酸、NAC1、乳酸、GPC和甘氨酸比起对照组来有显著上升,而葡萄糖、谷氨酰胺、亮氨酸、异亮氨酸、缬氨酸、丙酮、乙酰乙酸和苏氨酸则显著下降。而在不同分期肺腺癌患者间进行比较后发现,异亮氨酸、乙酰乙酸、NAC1和乳酸的变化与肺腺癌的发展有相关性,可能是肺腺癌早期诊断和分期的潜在生物标志物。     

LKB1 in lung cancerigenesis: a serine/threonine kinase as tumor suppressor

Lung cancer is featured with high mortality, with a 15% five-year survival rate worldwide. Genetic alterations, such as loss of function of tumor suppressor genes, frequently contribute to lung cancer initiation, progression and metastasis. Liver kinase B1 (LKB1), as a serine/threonine kinase and tumor suppressor, is frequently mutated and inactivated in non-small cell lung cancer (NSCLC). Recent studies have provided strong evidences that LKB1 loss promotes lung cancerigenesis process, especially lung cancer progression and metastasis. This review will summarize recent progress on how LKB1 modulates the process of lung cancerigenesis, emphasizing on LKB1 downstream signaling pathways and biological functions. We will further discuss the potential development of prognostic biomarkers or therapeutic targets in lung cancer clinic based on the molecular alteration associated with deregulated LKB1 signaling.     

Proteomic approaches to biomarker discovery in lung cancers by SELDI technology

The purpose of the present work is to identify protein profiles that could be used to discover specific biomarkers in serum and discriminate lung cancer. Thirty serum samples from patients with lung cancer (15 cases of primary brochogenic carcinoma, 9 cases of metastasis lung cancer and 6 cases of lung cancer after chemotherapy) and twelve from healthy individuals were analyzed by SELDI (Surfaced Enhanced Laser Desorption/Ionization) technology. Anion-exchange columns were used to fractionate the sera with 6 designated pH washing solutions. Two types of protein chip arrays, IMAC-Cu and WCX2, were employed. Protein chips were examined in PBSII ProteinChip Reader (Ciphergen Biosystems Inc.) and the resulting profiles between cancer and normal were analyzed with Biomarker Wizard System. In total, 15 potential lung cancer biomarkers, of which 6 were up-regulated and 9 were down-regulated, were discovered in the serum samples from patients with lung cancer. 5 of 15 these biomarkers were able to be detected on both WCX2 and IMAC-Cu protein chips. The sensitivities provided by the individual markers range from 44.8% to 93.1% and the specificities were 85.0%–94.4%. Our results suggest that serum is a capable resource for detection of lung cancer with specific biomarkers. Moreover, protein chip array system was shown to be a useful tool for identification, as well as detection of disease biomarkers in sera.     

Proteomic approaches to biomarker discovery in lung cancers by SELDI technology

Lung cancer is one of the most common tumors all over the world and one of those with higher mortality in clinic. For instance, 169500 new cases of lung cancer were estimated in the United States for 2001[1]. In recent years, both morbidity and mortality of lung cancer were reported gradually increasing in our country. Therefore, it has become an urgent task to search and discover specific biomarkers for lung cancer. In tumor genesis, certain cellular proteins must have changed their express…     

Galectin-4, a Novel Predictor for Lymph Node Metastasis in Lung Adenocarcinoma

Metastasis is still a major issue in cancer, and the discovery of biomarkers predicting metastatic capacity is essential for the development of better therapeutic strategies for treating lung adenocarcinoma. By using a proteomic approach, we aimed to identify novel predictors for lymph node metastasis in lung adenocarcinoma. Two-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis showed 6 spots differentially expressed between lymph node metastasis-positive and lymph node metastasis-negative groups in a discovery set. Subsequent mass spectrometry showed that 2 of these spots were derived from galectin-4, and western blot analysis confirmed the overexpression of galectin-4 in metastatic samples. The predictive value of galectin-4 was confirmed by immunohistochemical analysis for a validation set consisting of 707 surgically resected specimens of lung adenocarcinomas (stages I to IV). We observed that 148 lung adenocarcinomas (20.9%) expressed galectin-4, which was significantly associated with variables of disease progression such as tumor size (p<0.0001), pleural invasion (p = 0.0071), venous invasion (p = 0.0178), nodal status (p = 0.0007), and TNM stage (p<0.0001). By the multivariate analysis, Galectin-4 expression was revealed as one of the independent predictor for lymph node metastasis, together with solid predominant and micropapillary histologic pattern. Furthermore, galectin-4 expression was revealed to be an independent predictor for lymph node metastasis and an adverse survival factor in patients with lung adenocarcinoma of acinar predominant type. Galectin-4 plays an important role in metastatic process of lung adenocarcinoma. Immunohistochemical testing for galectin-4 expression may be useful together with the detection of specific histology to predict the metastatic potential of lung adenocarcinoma.     

Proteomic analysis of human saliva from lung cancer patients using two-dimensional difference gel electrophoresis and mass spectrometry

Lung cancer is often asymptomatic or causes only nonspecific symptoms in its early stages. Early detection represents one of the most promising approaches to reduce the growing lung cancer burden. Human saliva is an attractive diagnostic fluid because its collection is less invasive than that of tissue or blood. Profiling of proteins in saliva over the course of disease progression could reveal potential biomarkers indicative of oral or systematic diseases, which may be used extensively in future medical diagnostics. There were 72 subjects enrolled in this study for saliva sample collection according to the approved protocol. Two-dimensional difference gel electrophoresis combined with MS was the platform for salivary proteome separation, quantification, and identification from two pooled samples. Candidate proteomic biomarkers were verified and prevalidated by using immunoassay methods. There were 16 candidate protein biomarkers discovered by two-dimensional difference gel electrophoresis and MS. Three proteins were further verified in the discovery sample set, prevalidation sample set, and lung cancer cell lines. The discriminatory power of these candidate biomarkers in lung cancer patients and healthy control subjects can reach 88.5% sensitivity and 92.3% specificity with AUC = 0.90. This preliminary data report demonstrates that proteomic biomarkers are present in human saliva when people develop lung cancer. The discriminatory power of these candidate biomarkers indicate that a simple saliva test might be established for lung cancer clinical screening and detection.     

Comprehensive proteome analysis of malignant pleural effusion for lung cancer biomarker discovery by using multidimensional protein identification technology

Malignant pleural effusion (MPE) obtained from lung adenocarcinoma may contain potentially useful biomarkers for detection of lung cancer. In this study, we used a removal system for high-abundance proteins followed by one-dimensional SDS-PAGE combined with nano-LC-MS/MS to generate a comprehensive MPE proteome data set with 482 nonredundant proteins. Next, we integrated the MPE proteome and secretome data sets from three adenocarcinoma cell lines, with a view to identifying potential PE biomarkers originating from malignant cells. Four potential candidates, alpha-2-HS-glycoprotein (AHSG), angiogenin, cystatin-C, and insulin-like growth factor-binding protein 2, (IGFBP2), were isolated for preclinical validation using ELISA. Both AHSG and IGFBP2 levels were increased in lung patients with MPE (n = 68), compared to those with nonmalignant pleural effusion (n = 119). Notably, the IGFBP2 level was higher in MPE, compared with that in benign diseases (bacteria pneumonia and tuberculosis pleuritis), and significantly associated with malignancy, regardless of the cancer type. Our data additionally support an extracellular function of IGFBP2 in migration in lung cancer cells. These findings collectively suggest that the adenocarcinoma MPE proteome provides a useful data set for malignancy biomarker research.     

Synthesis and antitumor activities of novel α-aminophosphonates dehydroabietic acid derivatives

A series of novel α-aminophosphonate derivatives containing DHA structure were designed and synthesized as antitumor agents. In vitro antitumor activities of these compounds against the NCI-H460 (human lung cancer cell), A549 (human lung adenocarcinoma cell), HepG2 (human liver cancer cell) and SKOV3 (human ovarian cancer cell) human cancer cell lines were evaluated and compared with commercial anticancer drug 5-fluorouracil (5-FU), employing standard MTT assay. The pharmacological screening results revealed that many compounds exhibited moderate to high levels of antitumor activities against the tested cancer cell lines and that most demonstrated more potent inhibitory activities compared with the commercial anticancer drug 5-FU. The action mechanism of representative compound 7c was preliminarily investigated by acridine orange/ethidium bromide staining, Hoechst 33258 staining, JC-1 mitochondrial membrane potential staining and flow cytometry, which indicated that the compound can induce cell apoptosis in NCI-H460 cells. Cell cycle analysis showed that compound 7c mainly arrested NCI-H460 cells in G1 stage.